Challenges in validating CFD-derived inhaled aerosol deposition predictions.

Area of Science:

• Biomedical Engineering
• Computational Science
• Respiratory Medicine

Background:

• Computational Fluid Dynamics (CFD) offers advanced methods for studying inhaled particle deposition in human airways.
• Recent studies on aerosol deposition predictions using CFD models reveal significant challenges in their validation.
• The interpretation of 'validation' varies across disciplines, lacking a universal consensus for CFD models.

Purpose of the Study:

• To highlight the challenges in validating local aerosol deposition predictions from CFD models.
• To discuss the ambiguities in defining 'validation' for CFD models in airway deposition research.
• To identify necessary experimental data and matching conditions for validating CFD predictions.

Main Methods:

• Review of current literature on CFD model validation for aerosol deposition.
• Analysis of challenges in defining validation criteria and experimental data requirements.
• Discussion of potential discrepancies between total and local particle deposition predictions.

Main Results:

• A lack of consensus exists regarding the definition of a validated CFD model for aerosol deposition.
• Uncertainty remains on the specific types of experimental data and condition matching required for validation.
• CFD models may accurately predict total deposition while inaccurately representing local deposition patterns.

Conclusions:

• Establishing clear validation protocols for CFD models in aerosol science is crucial.
• Further research is needed to standardize experimental data and matching conditions for CFD model validation.
• Addressing these challenges will improve the reliability of CFD predictions for inhaled particle deposition.